Abstract

Massively parallel sequencing technology has catalyzed the discovery of genetic alterations that drive tumor initiation and progression. Efforts to comprehensively characterize the genomes of the most common tumor types have revealed recurrent alterations, many of which may be suppressed by targeted therapies. Moreover, through retrospective analysis of clinically annotated tumor specimens, one can identify genomic biomarkers that correlate with outcomes and therapeutic response. Profiling multiple tumors from individual patients at different sites or time points can reveal factors that influence clonal evolution and the onset of drug resistance. Finally, the prospective analysis of tumors in clinical laboratories can meaningfully influence the routine diagnosis and treatment of cancer patients. This promises to improve treatment decisions and to pre-identify patients eligible for future clinical trials of targeted therapies. Clinical labs have traditionally relied upon low-throughput capillary DNA sequencing and multiplexed base-pair genotyping (e.g. Sequenom). Massively parallel sequencing offers several key advantages over conventional mutation profiling strategies: 1) many more genes can be interrogated simultaneously; 2) entire exons can be sequenced, rather than pre-specified mutational hotspots, enabling complete characterization of tumor suppressor genes where mutations tend to be scattered; 3) structural aberrations such as gene amplification, deletions, and rearrangements can be simultaneously monitored; and 4) mutations at low allelic frequencies in heterogeneous tumors are more readily detected with high sensitivity. For increasingly lower costs, one can interrogate all clinically relevant genes for mutations, copy number alterations, and structural rearrangements in formalin-fixed paraffin embedded tumor tissue. We have developed a multiplexed massively parallel sequencing assay utilizing solution-phase exon capture of >300 cancer associated genes, which we have deployed both retrospectively and prospectively to profile more than 1,000 patients in a research setting. I will describe examples in which our group has identified genomic biomarkers predictive of drug response and resistance in a variety of tumor types. Additionally, I will discuss our progress in adapting this platform for clinical sequencing, compliant with federal and New York state regulations. Finally, I will describe general challenges in the establishment of clinical sequencing workflows involving bioinformatics, scalability, clinical interpretation, reporting, regulatory compliance, reimbursement, and ethics.